Relatedness Between Murray Cod Larvae 2011-2013 iGraph Plots
Alan Couch
Sat Jun 25 9:58:59 AM 2016
## Loading required package: knitr## Loading project configuration## Autoloading helper functions## Running helper script: funRel.R## Autoloading cache## Autoloading data## Loading data set: DARTallIdentifiers## Loading data set: qslAllLarvaInfo## Loading data set: qslMetaLarvAndAdultsUnion## Loading data set: qslMPeeliiForRelated## Loading data set: Report.DMac15.1861## Munging data## Running preprocessing script: 01MungeGeneticsDatacontaminationfix.R## Loading required package: dplyr##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, union## Running preprocessing script: 02MungeLarvaSnpsByYears.R## Running preprocessing script: 03MungeLarvaSnpsByYearCombos.Ra<-suppressPackageStartupMessages({
library(dplyr)
library(igraph)
library(ggplot2)
})
ptm <- proc.time()This uses iGraph to plot relatedness between larvae within each year so as to identify full sibling pairs(FS) and perhaps half sibling pairs (HS). Unrelated (US) is also calculated by the ‘r’ package ‘related’. However we are interested only in FS at this stage to identify common parents and to assist with determining the distance of larval dispersal.
The same is finally ploted for all three years combined.
First choose state which estimatore we are to use. (see compareEstimators)
estimator=5 #5-trioml,6-wang,7-lynchli,8-lynchrd,9-ritland,10-quellergt,11-dyadml
estimatorName="trioml" # change as needed with above
#Also choose which cutoffs to use. These are dependant on density plots
fshsCut<-0.4
hsurCut<-0.172011 Larval Relatedness Plots
main="2011 Larval snps"
fileName=paste("./outData/",main," coancestoryOutput", sep="")
load(file = fileName)require(igraph)
relData <- output$relatedness[, c(2, 3, estimator)]
hist(relData[, 3], main = "Histogram of estimator")
lrelData <- relData
colnames(lrelData)[1] <- "from"
colnames(lrelData)[2] <- "to"
colnames(lrelData)[3] <- "weight"
lrelData$type <- "probRel"
relDataNoRows <- nrow(relData)
nrelData <- data.frame(matrix(ncol = 4, nrow = relDataNoRows))
colnames(nrelData) <- c("id", "name", "type", "label")
nrelData[, 1] <- relData[, 2]
nrelData[, 2] <- relData[, 2]
newrow = c(relData[1, 1], relData[1, 1], NA, NA)
nrelData = rbind(nrelData, newrow)
nrow(nrelData)## [1] 1892length(unique(nrelData$id))## [1] 62nrow(lrelData)## [1] 1891nrow(unique(lrelData[, c("from", "to")]))## [1] 1891nrelData <- data.frame(unique(nrelData[, 1:4]))
tst <- ifelse(grepl("^A", nrelData$id), nrelData$type <- "adult", nrelData$type <- "larvae")
nrelData$type <- tst
rm(tst)
larvNrel <- merge(nrelData, larv, by.x = "id", by.y = "LarvalRecords_LarvaID")
larvNrel <- larvNrel[, c(1:4, 66)]
head(nrelData)## id name type label
## 1 71 71 larvae <NA>
## 2 72 72 larvae <NA>
## 3 73 73 larvae <NA>
## 4 76 76 larvae <NA>
## 5 75 75 larvae <NA>
## 6 74 74 larvae <NA>head(larvNrel)## id name type label YearOnly
## 1 100 100 larvae <NA> 2011
## 2 101 101 larvae <NA> 2011
## 3 103 103 larvae <NA> 2011
## 4 104 104 larvae <NA> 2011
## 5 105 105 larvae <NA> 2011
## 6 107 107 larvae <NA> 2011net <- graph_from_data_frame(d = lrelData, vertices = larvNrel, directed = FALSE)
fileName = paste("./outData/", main, " net", sep = "", collapse = " ")
save(net, file = fileName)Refine set and Plot relationships
fileName=paste("./outData/",main," net",sep="")
load(file = fileName)
#Limit to full siblings - this also makes it more sparse.
net.FS <- delete_edges(net, E(net)[weight<fshsCut])
l <- layout_with_fr(net.FS)
V(net.FS)$color=V(net.FS)$YearOnly #assign the "YearOnly" attribute as the vertex color
V(net.FS)$color=gsub("2011","indianred",V(net.FS)$color) #2011 will be red
V(net.FS)$color=gsub("2012","lightgoldenrod1",V(net.FS)$color) #2012 will be blue
V(net.FS)$color=gsub("2013","lightgreen",V(net.FS)$color) #2013 will be blue
E(net.FS)$weight<-E(net.FS)$weight*5
plot(net.FS, edge.arrow.size=0, edge.curved=0.2, vertex.size=5, vertex.color=V(net.FS)$color,vertex.frame.color="#555555",vertex.label=V(net)$name, vertex.label.color="black",vertex.label.cex=.7,edge.width=E(net.FS)$weight,layout=l)
#removed main=main;added edge.width=E(net.FS)$weight
title(paste(estimatorName,main),cex.main=3)
legend(x=-1.5, y=-1.1, c("2011","2012", "2013"), pch=21,col="#777777", cex=.8, bty="n", ncol=1)
2012 Larval Relatedness Plots
main="2012 Larval snps"
load(file = paste("./outData/",main," coancestoryOutput", sep=""))require(igraph)
relData <- output$relatedness[, c(2, 3, estimator)]
hist(relData[, 3], main = "Histogram of estimator")
lrelData <- relData
colnames(lrelData)[1] <- "from"
colnames(lrelData)[2] <- "to"
colnames(lrelData)[3] <- "weight"
lrelData$type <- "probRel"
relDataNoRows <- nrow(relData)
nrelData <- data.frame(matrix(ncol = 4, nrow = relDataNoRows))
colnames(nrelData) <- c("id", "name", "type", "label")
nrelData[, 1] <- relData[, 2]
nrelData[, 2] <- relData[, 2]
newrow = c(relData[1, 1], relData[1, 1], NA, NA)
nrelData = rbind(nrelData, newrow)
nrow(nrelData)## [1] 991length(unique(nrelData$id))## [1] 45nrow(lrelData)## [1] 990nrow(unique(lrelData[, c("from", "to")]))## [1] 990nrelData <- data.frame(unique(nrelData[, 1:4]))
tst <- ifelse(grepl("^A", nrelData$id), nrelData$type <- "adult", nrelData$type <- "larvae")
nrelData$type <- tst
rm(tst)
larvNrel <- merge(nrelData, larv, by.x = "id", by.y = "LarvalRecords_LarvaID")
larvNrel <- larvNrel[, c(1:4, 66)]
head(nrelData)## id name type label
## 1 151 151 larvae <NA>
## 2 157 157 larvae <NA>
## 3 156 156 larvae <NA>
## 4 155 155 larvae <NA>
## 5 154 154 larvae <NA>
## 6 153 153 larvae <NA>head(larvNrel)## id name type label YearOnly
## 1 134 134 larvae <NA> 2012
## 2 135 135 larvae <NA> 2012
## 3 136 136 larvae <NA> 2012
## 4 137 137 larvae <NA> 2012
## 5 138 138 larvae <NA> 2012
## 6 139 139 larvae <NA> 2012net <- graph_from_data_frame(d = lrelData, vertices = larvNrel, directed = FALSE)
fileName = paste("./outData/", main, " net", sep = "", collapse = " ")
save(net, file = fileName)Refine set and Plot relationships
fileName=paste0("outData/",main," net",sep=" ")
load(fileName)
#Limit to full siblings - this also makes it more sparse.
net.FS <- delete_edges(net, E(net)[weight<fshsCut])
l <- layout_with_fr(net.FS)
V(net.FS)$color=V(net.FS)$YearOnly #assign the "YearOnly" attribute as the vertex color
V(net.FS)$color=gsub("2011","indianred",V(net.FS)$color) #2011 will be red
V(net.FS)$color=gsub("2012","lightgoldenrod1",V(net.FS)$color) #2012 will be blue
V(net.FS)$color=gsub("2013","lightgreen",V(net.FS)$color) #2013 will be blue
E(net.FS)$weight<-E(net.FS)$weight*5
plot(net.FS, edge.arrow.size=0, edge.curved=0.2, vertex.size=5, vertex.color=V(net.FS)$color,vertex.frame.color="#555555",vertex.label=V(net)$name, vertex.label.color="black",vertex.label.cex=.7,edge.width=E(net.FS)$weight,layout=l)
#removed main=main;added edge.width=E(net.FS)$weight
title(paste(estimatorName,main),cex.main=3)
legend(x=-1.5, y=-1.1, c("2011","2012", "2013"), pch=21,col="#777777", cex=.8, bty="n", ncol=1)
2013 Larval Relatedness Plots
main="2013 Larval snps"
load(file = paste("./outData/",main," coancestoryOutput", sep=""))require(igraph)
relData <- output$relatedness[, c(2, 3, estimator)]
hist(relData[, 3], main = "Histogram of estimator")
lrelData <- relData
colnames(lrelData)[1] <- "from"
colnames(lrelData)[2] <- "to"
colnames(lrelData)[3] <- "weight"
lrelData$type <- "probRel"
relDataNoRows <- nrow(relData)
nrelData <- data.frame(matrix(ncol = 4, nrow = relDataNoRows))
colnames(nrelData) <- c("id", "name", "type", "label")
nrelData[, 1] <- relData[, 2]
nrelData[, 2] <- relData[, 2]
newrow = c(relData[1, 1], relData[1, 1], NA, NA)
nrelData = rbind(nrelData, newrow)
nrow(nrelData)## [1] 8516length(unique(nrelData$id))## [1] 131nrow(lrelData)## [1] 8515nrow(unique(lrelData[, c("from", "to")]))## [1] 8515nrelData <- data.frame(unique(nrelData[, 1:4]))
tst <- ifelse(grepl("^A", nrelData$id), nrelData$type <- "adult", nrelData$type <- "larvae")
nrelData$type <- tst
rm(tst)
larvNrel <- merge(nrelData, larv, by.x = "id", by.y = "LarvalRecords_LarvaID")
larvNrel <- larvNrel[, c(1:4, 66)]
head(nrelData)## id name type label
## 1 186 186 larvae <NA>
## 2 187 187 larvae <NA>
## 3 188 188 larvae <NA>
## 4 189 189 larvae <NA>
## 5 190 190 larvae <NA>
## 6 191 191 larvae <NA>head(larvNrel)## id name type label YearOnly
## 1 185 185 larvae <NA> 2013
## 2 186 186 larvae <NA> 2013
## 3 187 187 larvae <NA> 2013
## 4 188 188 larvae <NA> 2013
## 5 189 189 larvae <NA> 2013
## 6 190 190 larvae <NA> 2013net <- graph_from_data_frame(d = lrelData, vertices = larvNrel, directed = FALSE)
fileName = paste("./outData/", main, " net", sep = "", collapse = " ")
save(net, file = fileName)Refine set and Plot relationships
fileName=paste("./outData/",main," net",sep="")
load(file = fileName)
#Limit to full siblings - this also makes it more sparse.
net.FS <- delete_edges(net, E(net)[weight<fshsCut])
l <- layout_with_fr(net.FS)
V(net.FS)$color=V(net.FS)$YearOnly #assign the "YearOnly" attribute as the vertex color
V(net.FS)$color=gsub("2011","indianred",V(net.FS)$color) #2011 will be red
V(net.FS)$color=gsub("2012","lightgoldenrod1",V(net.FS)$color) #2012 will be blue
V(net.FS)$color=gsub("2013","lightgreen",V(net.FS)$color) #2013 will be blue
E(net.FS)$weight<-E(net.FS)$weight*5
plot(net.FS, edge.arrow.size=0, edge.curved=0.2, vertex.size=5, vertex.color=V(net.FS)$color,vertex.frame.color="#555555",vertex.label=V(net)$name, vertex.label.color="black",vertex.label.cex=.7,edge.width=E(net.FS)$weight,layout=l)
#removed main=main;added edge.width=E(net.FS)$weight
title(paste(estimatorName,main),cex.main=3)
legend(x=-1.5, y=-1.1, c("2011","2012", "2013"), pch=21,col="#777777", cex=.8, bty="n", ncol=1)
2011-2013 Larval Relatedness Plots
main="2011-2013 Larval snps"
load(file = paste("./outData/",main," coancestoryOutput", sep=""))require(igraph)
relData <- output$relatedness[, c(2, 3, estimator)]
hist(relData[, 3], main = "Histogram of estimator")
lrelData <- relData
colnames(lrelData)[1] <- "from"
colnames(lrelData)[2] <- "to"
colnames(lrelData)[3] <- "weight"
lrelData$type <- "probRel"
relDataNoRows <- nrow(relData)
nrelData <- data.frame(matrix(ncol = 4, nrow = relDataNoRows))
colnames(nrelData) <- c("id", "name", "type", "label")
nrelData[, 1] <- relData[, 2]
nrelData[, 2] <- relData[, 2]
newrow = c(relData[1, 1], relData[1, 1], NA, NA)
nrelData = rbind(nrelData, newrow)
nrow(nrelData)## [1] 28204length(unique(nrelData$id))## [1] 238nrow(lrelData)## [1] 28203nrow(unique(lrelData[, c("from", "to")]))## [1] 28203nrelData <- data.frame(unique(nrelData[, 1:4]))
tst <- ifelse(grepl("^A", nrelData$id), nrelData$type <- "adult", nrelData$type <- "larvae")
nrelData$type <- tst
rm(tst)
larvNrel <- merge(nrelData, larv, by.x = "id", by.y = "LarvalRecords_LarvaID")
larvNrel <- larvNrel[, c(1:4, 66)]
head(nrelData)## id name type label
## 1 186 186 larvae <NA>
## 2 187 187 larvae <NA>
## 3 188 188 larvae <NA>
## 4 189 189 larvae <NA>
## 5 190 190 larvae <NA>
## 6 191 191 larvae <NA>head(larvNrel)## id name type label YearOnly
## 1 100 100 larvae <NA> 2011
## 2 101 101 larvae <NA> 2011
## 3 103 103 larvae <NA> 2011
## 4 104 104 larvae <NA> 2011
## 5 105 105 larvae <NA> 2011
## 6 107 107 larvae <NA> 2011net <- graph_from_data_frame(d = lrelData, vertices = larvNrel, directed = FALSE)
fileName = paste("./outData/", main, " net", sep = "", collapse = " ")
save(net, file = fileName)Refine set and Plot relationships
fileName=paste("./outData/",main," net",sep="")
load(file = fileName)
#Limit to full siblings - this also makes it more sparse.
net.FS <- delete_edges(net, E(net)[weight<fshsCut])
l <- layout_with_fr(net.FS)
V(net.FS)$color=V(net.FS)$YearOnly #assign the "YearOnly" attribute as the vertex color
V(net.FS)$color=gsub("2011","indianred",V(net.FS)$color) #2011 will be red
V(net.FS)$color=gsub("2012","lightgoldenrod1",V(net.FS)$color) #2012 will be blue
V(net.FS)$color=gsub("2013","lightgreen",V(net.FS)$color) #2013 will be blue
E(net.FS)$weight<-E(net.FS)$weight*5
plot(net.FS, edge.arrow.size=0, edge.curved=0.2, vertex.size=5, vertex.color=V(net.FS)$color,vertex.frame.color="#555555",vertex.label=V(net)$name, vertex.label.color="black",vertex.label.cex=.7,edge.width=E(net.FS)$weight,layout=l)
#removed main=main;added edge.width=E(net.FS)$weight
title(paste(estimatorName,main),cex.main=3)
legend(x=-1.5, y=-1.1, c("2011","2012", "2013"), pch=21,col="#777777", cex=.8, bty="n", ncol=1)
2011-2013 Larvae Relatedness with Adults
main="2011-2013 Larval snps with Adults"
load(file = paste("./outData/",main," coancestoryOutput", sep=""))require(igraph)
relData <- output$relatedness[, c(2, 3, estimator)]
hist(relData[, 3])
lrelData <- relData
colnames(lrelData)[1] <- "from"
colnames(lrelData)[2] <- "to"
colnames(lrelData)[3] <- "weight"
lrelData$type <- "probRel"
relDataNoRows <- nrow(relData)
nrelData <- data.frame(matrix(ncol = 4, nrow = relDataNoRows))
colnames(nrelData) <- c("id", "name", "type", "label")
nrelData[, 1] <- relData[, 2]
nrelData[, 2] <- relData[, 2]
newrow = c(relData[1, 1], relData[1, 1], NA, NA)
nrelData = rbind(nrelData, newrow)
nrow(nrelData)## [1] 34454length(unique(nrelData$id))## [1] 263nrow(lrelData)## [1] 34453nrow(unique(lrelData[, c("from", "to")]))## [1] 34453nrelData <- data.frame(unique(nrelData[, 1:4]))
tst <- ifelse(grepl("^A", nrelData$id), nrelData$type <- "adult", nrelData$type <- "larvae")
nrelData$type <- tst
rm(tst)
larvNrel <- merge(nrelData, qslMetaLarvAndAdultsUnion, by = "id")
head(nrelData)## id name type label
## 1 186 186 larvae <NA>
## 2 187 187 larvae <NA>
## 3 188 188 larvae <NA>
## 4 189 189 larvae <NA>
## 5 190 190 larvae <NA>
## 6 191 191 larvae <NA>head(larvNrel)## id name type label pop YearOnly hatchDoY lat lon Site.Name catchDoY estimatedAge mother father
## 1 100 100 larvae <NA> M. peelii 2011 309.1240 -35.43 149.07 Murramore 326 9.39 MH6 FH6
## 2 101 101 larvae <NA> M. peelii 2011 309.8434 -35.43 149.07 Murramore 326 8.67
## 3 103 103 larvae <NA> M. peelii 2011 297.4343 -35.43 149.07 Murramore 326 21.08
## 4 104 104 larvae <NA> M. peelii 2011 308.7643 -35.43 149.07 Murramore 326 9.75 MH6 FH6
## 5 105 105 larvae <NA> M. peelii 2011 318.9451 -35.43 149.07 Murramore 340 11.73 Gilly Samwell
## 6 107 107 larvae <NA> M. peelii 2011 309.6635 -35.43 149.07 Murramore 326 8.85 MH6 FH6net <- graph_from_data_frame(d = lrelData, vertices = nrelData, directed = FALSE)
fileName = paste("./outData/", main, " net", sep = "", collapse = " ")
save(net, file = fileName)Refine set and Plot relationships
fileName=paste("./outData/","2011-2013 Larval snps with Adults"," net",sep="")
load(file = fileName)
#Limit to full siblings - this also makes it more sparse.
net.FS <- delete_edges(net, E(net)[weight<fshsCut])
l <- layout_with_fr(net.FS)
plot(net.FS, edge.arrow.size=0, edge.curved=0, vertex.size=5,vertex.color=c("orange", "cyan")[(V(net.FS)$type=="larvae")+1], vertex.frame.color="#555555",vertex.label=V(net)$name, vertex.label.color="black",vertex.label.cex=.7,layout=l)
title(paste(estimatorName,main),cex.main=3)
2011-2013 Larvae with Parents
#Prepare data
prelDataA<-cbind(larvNrel[,c(1,13)],rep("1",nrow(larvNrel)),rep("mother",nrow(larvNrel)))
colnames(prelDataA)[1]<-"from"
colnames(prelDataA)[2]<-"to"
colnames(prelDataA)[3]<-"weight"
colnames(prelDataA)[4]<-"type"
prelDataB<-cbind(larvNrel[,c(1,14)],rep("1",nrow(larvNrel)),rep("father",nrow(larvNrel)))
colnames(prelDataB)[1]<-"from"
colnames(prelDataB)[2]<-"to"
colnames(prelDataB)[3]<-"weight"
colnames(prelDataB)[4]<-"type"
prelData<-rbind(prelDataA,prelDataB)
prelData[prelData==""] <- NA
rm(prelDataB);rm(prelDataA)
tmp<-prelData[complete.cases(prelData),]
#Create Vertices Data Frame
prelVert <- data.frame(matrix(ncol = 4, nrow = nrow(tmp)))
colnames(prelVert) <- c("id", "name", "type", "label")
prelVert$id<-tmp$to
prelVert$name<-tmp$to
prelVert$type<-tmp$type
prelVert<-rbind(prelVert, nrelData)
prelVert<-unique(prelVert)
prelData<-prelData[complete.cases(prelData),]
prelData <- subset(prelData, !from == 177) #these line needed to remove a few potential contaminants
prelData <- subset(prelData, !from == 314) #although I doubt there was actually contam as the otherhs are the same.
prelData <- subset(prelData, !from == 366)
require(igraph)
net.parents<-graph_from_data_frame(d=prelData, vertices=prelVert, directed=FALSE)
l <- layout_with_fr(net.parents)
#Colour vertices :parents and larvae
V(net.parents)$color=V(net.parents)$type #assign the "type" attribute as the vertex color then assign a colour based on that type.
V(net.parents)$color=gsub("mother","lightpink",V(net.parents)$color)
V(net.parents)$color=gsub("father","lightblue",V(net.parents)$color)
V(net.parents)$color=gsub("larvae","lightgreen",V(net.parents)$color)
V(net.parents)$color=gsub("adult","orange",V(net.parents)$color)
plot(net.parents, edge.arrow.size=0, edge.curved=0, vertex.size=5, vertex.color=V(net.parents)$color,vertex.frame.color="#555555",vertex.label=V(net.parents)$name, vertex.label.color="black",vertex.label.cex=.7,layout=l, main = "Full Siblings With Parents")
2011-2013 With Parents but only half-sib links
##Now to add in sib weights so we can include half sibs and exclude full sib edges.
prelData$weight<-as.numeric(as.character(prelData$weight))
allData<-rbind(prelData, lrelData)
allData<-allData[complete.cases(allData),]
net.all<-graph_from_data_frame(d=allData, vertices=prelVert, directed=FALSE)
#set parmeters for edges to delete (so they dont show and clutter the graph)
net.all <- delete_edges(net.all, E(net.all)[weight>0.379])
net.all <- delete_edges(net.all, E(net.all)[weight<0.2])
#to colour half sibling edges according to weight
E(net.all)[ weight > .34 ]$color <- "darkgreen"
E(net.all)[ weight < .3 ]$color <- "green"
E(net.all)[ weight < .24 ]$color <- "yellow"
#to colour parents and larvae
V(net.all)$color=V(net.all)$type #assign the "type" attribute as the vertex color
V(net.all)$color=gsub("mother","lightpink",V(net.all)$color) #mums will be pink
V(net.all)$color=gsub("father","lightblue",V(net.all)$color) #dads will be blue
V(net.all)$color=gsub("larvae","lightgreen",V(net.all)$color) #larvae will be green
V(net.all)$color=gsub("adult","orange",V(net.all)$color) #adult will be orange
plot(net.all, edge.arrow.size=0, edge.curved=0, vertex.size=5, vertex.color=V(net.all)$color,vertex.frame.color="#555555",vertex.label=V(net.all)$name, vertex.label.color="black",vertex.label.cex=.7,layout=l, main = "Half Siblings With Parents")
Coloured by Year
#Now another look coloured by Years
net.all<-graph_from_data_frame(d=allData, vertices=prelVert, directed=FALSE)
#set parmeters for edges to delete (so they dont show and clutter the graph)
net.all <- delete_edges(net.all, E(net.all)[weight>0.379])
net.all <- delete_edges(net.all, E(net.all)[weight<0.2])
#to colour half sibling edges according to weight
E(net.all)[ weight > .34 ]$color <- "darkgreen"
E(net.all)[ weight < .3 ]$color <- "green"
E(net.all)[ weight < .24 ]$color <- "yellow"
#to colour vertices by yearsparents and larvae
V(net.all)$color=gsub("mother","lightpink",V(net.all)$color) #mums will be pink
V(net.all)$color=gsub("father","lightblue",V(net.all)$color) #dads will be blue
V(net.all)[name<134]$color<-"red"#2011 will be red
V(net.all)[name>133]$color<-"yellow"#2012 will be yellow
V(net.all)[name>184]$color<-"lightgreen" #2013 will be green
plot(net.all, edge.arrow.size=0, edge.curved=0, vertex.size=5, vertex.color=V(net.all)$color,vertex.frame.color="#555555",vertex.label=V(net.all)$name, vertex.label.color="black",vertex.label.cex=.7,layout=l, main = "Half Siblings With Some Parents Coloured by Year")
Session Info
all_labels()## [1] "Project_Template_and_Knitr" "Set_Global_Options" "unnamed-chunk-1" "unnamed-chunk-2"
## [5] "Nominate Estimator to Use" "unnamed-chunk-3" "Larvae2011Net" "unnamed-chunk-4"
## [9] "unnamed-chunk-5" "Larvae2012Net" "unnamed-chunk-6" "unnamed-chunk-7"
## [13] "Larvae2013Net" "unnamed-chunk-8" "unnamed-chunk-9" "Larvae2011-2013Net"
## [17] "unnamed-chunk-10" "unnamed-chunk-11" "unnamed-chunk-12" "LarvaeAdults2011-2013Net"
## [21] "unnamed-chunk-13" "unnamed-chunk-14" "unnamed-chunk-15" "HalfSibsColouredByYear"
## [25] "Include_Chunk_Labels_and_Session Information" "createNet" "createNetA"proc.time()-ptm## user system elapsed
## 17.21 2.37 33.97#Session Information
sessionInfo()## R version 3.3.0 (2016-05-03)
## Platform: i386-w64-mingw32/i386 (32-bit)
## Running under: Windows 7 x64 (build 7601) Service Pack 1
##
## locale:
## [1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252 LC_MONETARY=English_Australia.1252 LC_NUMERIC=C LC_TIME=English_Australia.1252
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggplot2_2.1.0 igraph_1.0.1 dplyr_0.4.3 ProjectTemplate_0.6 knitr_1.13
##
## loaded via a namespace (and not attached):
## [1] Rcpp_0.12.5 digest_0.6.9 assertthat_0.1 plyr_1.8.4 grid_3.3.0 R6_2.1.2 gtable_0.2.0 DBI_0.4-1 formatR_1.4 magrittr_1.5 scales_0.4.0
## [12] evaluate_0.9 stringi_1.1.1 lazyeval_0.1.10 rmarkdown_0.9.6 tools_3.3.0 stringr_1.0.0 munsell_0.4.3 yaml_2.1.13 parallel_3.3.0 colorspace_1.2-6 htmltools_0.3.5